Tomas Cipra
Time Series in Economics and Finance
Time Series in Economics and Finance
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Excellent- More about Time Series in Economics and Finance
The book provides principles and methods for analyzing and predicting economic and financial time series, including decomposition methods, autocorrelation methods, volatility and duration modeling, and multivariate time series methods. It includes practical examples and exercises for understanding.
Format: Paperback / softback
Length: 410 pages
Publication date: 01 September 2021
Publisher: Springer Nature Switzerland AG
This comprehensive book delves into the realm of practical analysis and prediction of economic and financial time series. It offers a comprehensive framework that encompasses a wide range of methods and techniques to unravel the complexities of these dynamic datasets. The book begins by introducing the fundamental principles and concepts of time series analysis, including decomposition methods, autocorrelation methods for univariate time series, volatility and duration modeling for financial time series, and multivariate time series methods such as cointegration and recursive state space modeling.
To enhance understanding, the book provides numerous practical examples drawn from real-world data, showcasing the application of these theories in various economic and financial contexts. Each chapter concludes with a series of exercises designed to reinforce the key concepts and encourage hands-on practice.
Designed as a reference text for researchers, students, and practitioners alike, this book serves as a valuable resource for those interested in time series analysis. It is also an essential resource for university courses in econometrics and computational finance, providing a thorough and up-to-date coverage of the field.
By exploring the principles and methods outlined in this book, readers will gain a deep understanding of the techniques used to analyze and predict economic and financial time series, enabling them to make informed decisions based on data-driven insights.
Weight: 640g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030463496
Edition number: 1st ed. 2020
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